PubMed Health⌕ Search

PubMed · 10929695

Maintaining study validity in a changing clinical environment.

Abstract

BACKGROUND: Nurse scientists who conduct intervention research in a variety of clinical settings find themselves facing numerous challenges posed by today's changing and sometimes complex health care environment. Maintaining study validity thus becomes a major focus of interventional research, but existing literature does not fully address challenges to study validity nor offer potential solutions. OBJECTIVES: The purposes of this paper are to 1) discuss methodologic challenges to maintaining study validity of intervention research that is conducted in a changing clinical environment, and 2) share strategies for maximizing study validity. METHODS: A recently completed intervention study is used as an example to discuss two specific areas that affected study validity, provide examples of selected threats to validity, and outline strategies used to minimize these threats. RESULTS: Careful definition of goals, thoughtful decision making, and implementation of specific strategies to maintain study validity helped increased the rigor of the research. CONCLUSIONS: Investigators conducting intervention research in changing clinical settings can reduce threats to study validity and increase design rigor by considering clinical realities (e.g., clinician-researcher role conflict) when making methodologic decisions, becoming familiar with the setting, and involving clinicians in the research.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

D B McGuire, V G DeLoney, K A Yeager, D C Owen, D E Peterson, L S Lin, J Webster. Maintaining study validity in a changing clinical environment.. https://doi.org/10.1097/00006199-200007000-00007

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Missing covariate data within cancer prognostic studies: a review of current reporting and proposed guidelines.

Prognostic models play a crucial role in the clinical decision-making process. Unfortunately, missing covariate data impede the construction of valid and reliable models, potentially introducing bias, if handled inappropriately. The extent of missing covariate data within reported cancer prognostic studies, the current handling and the quality of reporting this missing covariate data are unknown. Therefore, a review was conducted of 100 articles reporting multivariate survival analyses to assess potential prognostic factors, published within seven cancer journals in 2002. Missing covariate data is a common occurrence in studies performing multivariate survival analyses, being apparent in 81 of the 100 articles reviewed. The percentage of eligible cases with complete data was obtainable in 39 articles, and was <90% in 17 of these articles. The methods used to handle incomplete covariates were obtainable in 32 of the 81 articles with known missing data and the most commonly reported approaches were complete case and available case analysis. This review has highlighted deficiencies in the reporting of missing covariate data. Guidelines for presenting prognostic studies with missing covariate data are proposed, which if followed should clarify and standardise the reporting in future articles.

Decision Making↗